Персона: Ильясов, Айдар Иршатович
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Институт ядерной физики и технологий
Цель ИЯФиТ и стратегия развития - создание и развитие научно-образовательного центра мирового уровня в области ядерной физики и технологий, радиационного материаловедения, физики элементарных частиц, астрофизики и космофизики.
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Ильясов
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Айдар Иршатович
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- ПубликацияТолько метаданныеPulse-shape discrimination against low-energy Ar-39 beta decays in liquid argon with 4.5 tonne-years of DEAP-3600 data(2021) Adhikari, P.; Ajaj, R.; Alpizar-Venegas, M.; Amaudruz, P. -A.; Grobov, A.; Ilyasov, A.; Levashko, N.; Machulin, I.; Ильясов, Айдар Иршатович; Мачулин, Игорь Николаевич© 2021, The Author(s).The DEAP-3600 detector searches for the scintillation signal from dark matter particles scattering on a 3.3 tonne liquid argon target. The largest background comes from 39Ar beta decays and is suppressed using pulse-shape discrimination (PSD). We use two types of PSD estimator: the prompt-fraction, which considers the fraction of the scintillation signal in a narrow and a wide time window around the event peak, and the log-likelihood-ratio, which compares the observed photon arrival times to a signal and a background model. We furthermore use two algorithms to determine the number of photons detected at a given time: (1) simply dividing the charge of each PMT pulse by the mean single-photoelectron charge, and (2) a likelihood analysis that considers the probability to detect a certain number of photons at a given time, based on a model for the scintillation pulse shape and for afterpulsing in the light detectors. The prompt-fraction performs approximately as well as the log-likelihood-ratio PSD algorithm if the photon detection times are not biased by detector effects. We explain this result using a model for the information carried by scintillation photons as a function of the time when they are detected.
- ПубликацияТолько метаданныеSiPM-matrix readout of two-phase argon detectors using electroluminescence in the visible and near infrared range(2021) Aalseth, C. E.; Abdelhakim, S.; Agnes, P.; Ajaj, R.; Grobov, A.; Ilyasov, A.; Levashko, N.; Machulin, I. N.; Skorokhvatov, M. D.; Ильясов, Айдар Иршатович; Мачулин, Игорь Николаевич; Скорохватов, Михаил Дмитриевич© 2021, The Author(s).Proportional electroluminescence (EL) in noble gases is used in two-phase detectors for dark matter searches to record (in the gas phase) the ionization signal induced by particle scattering in the liquid phase. The “standard” EL mechanism is considered to be due to noble gas excimer emission in the vacuum ultraviolet (VUV). In addition, there are two alternative mechanisms, producing light in the visible and near infrared (NIR) ranges. The first is due to bremsstrahlung of electrons scattered on neutral atoms (“neutral bremsstrahlung”, NBrS). The second, responsible for electron avalanche scintillation in the NIR at higher electric fields, is due to transitions between excited atomic states. In this work, we have for the first time demonstrated two alternative techniques of the optical readout of two-phase argon detectors, in the visible and NIR range, using a silicon photomultiplier matrix and electroluminescence due to either neutral bremsstrahlung or avalanche scintillation. The amplitude yield and position resolution were measured for these readout techniques, which allowed to assess the detection threshold for electron and nuclear recoils in two-phase argon detectors for dark matter searches. To the best of our knowledge, this is the first practical application of the NBrS effect in detection science.
- ПубликацияТолько метаданныеValidating Position Reconstruction Algorithm with Am–Be Neutron Source in DEAP-3600(2025) Grobov, A. V.; Ilyasov, A. I.; Ильясов, Айдар Иршатович
- ПубликацияТолько метаданныеPrecision measurement of the specific activity of 39 Ar in atmospheric argon with the DEAP-3600 detector(2023) Adhikari, P.; Ajaj, R.; Alpizar-Venegas, M.; Amaudruz, P. -A.; Ilyasov, A.; Levashko, N.; Machulin, I.; Ильясов, Айдар Иршатович; Мачулин, Игорь Николаевич
- ПубликацияТолько метаданныеDesign and construction of a new detector to measure ultra-low radioactive-isotope contamination of argon(2020) Aalseth, C. E.; Abdelhakim, S.; Acerbi, F.; Agnes, P.; Grobov, A.; Ilyasov, A.; Levashko, N.; Machulin, I. N.; Skorokhvatov, M. D.; Ильясов, Айдар Иршатович; Мачулин, Игорь Николаевич; Скорохватов, Михаил Дмитриевич© 2020 IOP Publishing Ltd and Sissa MedialabLarge liquid argon detectors offer one of the best avenues for the detection of galactic weakly interacting massive particles (WIMPs) via their scattering on atomic nuclei. The liquid argon target allows exquisite discrimination between nuclear and electron recoil signals via pulse-shape discrimination of the scintillation signals. Atmospheric argon (AAr), however, has a naturally occurring radioactive isotope, 39Ar, a β emitter of cosmogenic origin. For large detectors, the atmospheric 39Ar activity poses pile-up concerns. The use of argon extracted from underground wells, deprived of 39Ar, is key to the physics potential of these experiments. The DarkSide-20k dark matter search experiment will operate a dual-phase time projection chamber with 50 tonnes of radio-pure underground argon (UAr), that was shown to be depleted of 39Ar with respect to AAr by a factor larger than 1400. Assessing the 39Ar content of the UAr during extraction is crucial for the success of DarkSide-20k, as well as for future experiments of the Global Argon Dark Matter Collaboration (GADMC). This will be carried out by the DArT in ArDM experiment, a small chamber made with extremely radio-pure materials that will be placed at the centre of the ArDM detector, in the Canfranc Underground Laboratory (LSC) in Spain. The ArDM LAr volume acts as an active veto for background radioactivity, mostly γ-rays from the ArDM detector materials and the surrounding rock. This article describes the DArT in ArDM project, including the chamber design and construction, and reviews the background required to achieve the expected performance of the detector.
- ПубликацияТолько метаданныеПрименение машинного обучения для идентификации событий в эксперименте DarkSide-50(2020) Ильясов, А. И.; Ильясов, Айдар Иршатович; Гробов Алексей Викторович
- ПубликацияТолько метаданныеRecent results on a machine learning approach to event position reconstruction in the DEAP-3600 Dark Matter Search Experiment(2024) Ilyasov, A.; Ильясов, Айдар Иршатович
- ПубликацияТолько метаданныеThe DEAP-3600 Experiment(2022) Stringer, M.; Adhikari, P.; Ajaj, R.; Grobov, A.; Ilyasov, A.; Machulin, I.; Levashko, N.; Ильясов, Айдар Иршатович; Мачулин, Игорь НиколаевичThe DEAP-3600 experiment searches for dark matter via the interactions of WIMPs with a liquid argon target. The experiment is located at SNOLAB in Sudbury, Ontario, 2 km underground to shield the detector from cosmic rays. The detector consists of an acrylic sphere with an inner diameter of ∼170 cm containing ∼3300 kg of liquid argon. Liquid argon is chosen as a target due to its ability to reject electromagnetic backgrounds by examining its scintillation pulse shape. The argon volume is instrumented with 255 PMTs which are connected to the vessel via acrylic light guides. As liquid argon scintillates at a wavelength of 128 nm, its scintillation light needs to be shifted to a wavelength into a region where the PMTs are more sensitive; this is done by coating the inside of the acrylic vessel with TPB wavelength shifter, which re-emits the argon scintillation light at a wavelength of 420 nm. This talk will describe the current status of the experiment and some recent analyses performed by the collaboration. The status of planned upgrades to the detector and the plans for the future of the experiment will also be detailed. © Copyright owned by the author(s) under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND 4.0).
- ПубликацияТолько метаданныеBoosted decision trees approach to neck alpha events discrimination in DEAP-3600 experiment(2020) Grobov, A.; Ilyasov, A.; Ильясов, Айдар Иршатович© 2020 IOP Publishing Ltd.Machine learning (ML) has been widely applied in high energy physics to help the physical community in particle classification and data analysis. Here we describe the application of machine learning to solve the problem of classifying background and signal events for the DEAP-3600 dark matter search experiment (SNOLAB, Canada). We apply Boosted Decision Trees (BDT) algorithm of ML with improvements from Extra Trees and eXtra Gradient Boosting (XGBoost) methods [1, 2].
- ПубликацияТолько метаданныеПрименение свёрточных нейронных сетей для реконструкции положения события в эксперименте DEAP-3600(2021) Ильясов, А. И.; Ильясов, Айдар Иршатович; Гробов А.В.